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A comprehensive review on modelling the adsorption process for heavy metal removal from waste water using artificial neural network technique
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Publication Date
Wed May 10 2023
Journal Name
Journal Of Engineering
Irrigation Scheduling Effect on Water Requirements
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Irrigation scheduling techniques is one of the suggested solutions for water scarcity problem. The study aims to show the possibility of using practical and applicable irrigation scheduling program which was designed by Water Resources Department at the University of Baghdad by using Spreadsheet Formulas for Microsoft Excel program, version 2007, with some modification to generalize it and made it applicable to various climatic zone and different soil types, as a salvation for the shortage of irrigation water inside the irrigation projects. Irrigation projects which incidence of Tigris River basin will be taken as an applicable example. This program was based on water budgeting and programmed depending on scientific concepts which facili

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Publication Date
Wed Dec 13 2023
Journal Name
Iraqi Journal Of Architecture And Planning
Geospatial Techniques for Preparing the Requirements of 3D Modeling for Smart City Planning- Review paper
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Developing smart city planning requires integrating various techniques, including geospatial techniques, building information models (BIM), information and communication technology (ICT), and artificial intelligence, for instance, three-dimensional (3D) building models, in enabling smart city applications. This study aims to comprehensively analyze the role and significance of geospatial techniques in smart city planning and implementation. The literature review encompasses (74) studies from diverse databases, examining relevant solutions and prototypes related to smart city planning. The focus highlights the requirements and preparation of geospatial techniques to support the transition to a smart city. The paper explores various aspects,

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Publication Date
Sun Sep 01 2019
Journal Name
Https://iopscience.iop.org/journal/1742-6596
Heavy Metals Causing Toxicity in Fishes
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Abstract<p>The heavy metals mainly include Pb, Hg, Cd, Cr, Cu, Zn, Mn, Ni, Ag, etc. The heavy metals,Pb,Cu,Zn are considered most toxic to humans, fishes and environment. highly concentrations of heavy metals are harmful They destabilize ecosystems because of their bioaccumulation in organisms, and toxic effects on biota and even death in most living beings. All heavy metals, in spite some of them are essential micronutrients, have their toxic effects on living organisms via metabolic interference and mutagenesis. The bioaccumulation of toxic metals can happen in the body and food chain. So, the toxic metals generally exhibit chronic toxicity. The heavy metals like Pb has significant toxic effec</p> ... Show More
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Publication Date
Fri Sep 30 2011
Journal Name
Al-khwarizmi Engineering Journal
Upgrading Sharky Baghdad Heavy Crude Oil
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Shaky Baghdad heavy crude oil 22 API is processed by distillation and solvent extraction. The purpose of distillation is to separate the light distillates    (light fractions) which represent 35% of heavy crude oil, and to obtain the reduced crude oil. The heavy residue (9 API) is  extracted with Iraqi light naphtha to get the deasphaltened oil (DAO), the extraction carried out with temperature range of 20-75 oC, solvent to oil ratio 5-15:1(ml:g) and a mixing time of 15 minutes. In general, results show that API of DAO increased twice the API of reduced crude oil while sulfur and metals content decreased 20% and 50% respectively. Deasphaltened oil produced from various operating conditions blended with the

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Publication Date
Wed Sep 01 2010
Journal Name
Al-khwarizmi Engineering Journal
Prediction of the Scale Removal Rate in Heat Exchanger Piping System Using the Analogies between Mass and Momentum Transfer
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The possibility of predicting the mass transfer controlled CaCO3 scale removal   rate has been investigated.

Experiments were carried out using chelating agents as a cleaning solution at different time and Reynolds’s number. The results of CaCO3 scale removal or (mass transfer rate) (as it is the controlling process) are compared with proposed model of prandtl’s and Taylor particularly based on the concept of analogy among momentum and mass transfer.

Correlation for the variation of Sherwood number ( or mass transfer rate ) with Reynolds’s number have been obtained .

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Publication Date
Wed May 03 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Enhancing smart home energy efficiency through accurate load prediction using deep convolutional neural networks
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The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

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Publication Date
Tue Feb 01 2022
Journal Name
Journal Of Engineering Science And Technology
CORROSION of STEEL REINFORCEMENT in INTERNALLY CURED SELF-COMPACTING CONCRETE USING WASTE BRICK and THERMOSTONE
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Internal curing is a method that has been advised to decrease the primary age cracking, mainly of concrete mixes using low (water to cementitious materials - w/cm) ratios corresponding to the self-compacting concrete-(SCC). This research aims to study the effect of the internal curing using saturated lightweight aggregate- (LWA) on the steel reinforcing corrosion in SCC. In this research, crushed bricks or thermostone were partially replaced by (20%) by the weight of sand and volumetrically measured. The results showed that the steel reinforcement of internally cured concrete showed a slight increase in corrosion up to 300 days of exposure to the saline solution (containing 3.5% NaCl). The ability of using the crushed bricks or thermostone

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Publication Date
Tue Feb 01 2022
Journal Name
Journal Of Engineering Science And Technology
CORROSION of STEEL REINFORCEMENT in INTERNALLY CURED SELF-COMPACTING CONCRETE USING WASTE BRICK and THERMOSTONE
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Internal curing is a method that has been advised to decrease the primary age cracking, mainly of concrete mixes using low (water to cementitious materials - w/cm) ratios corresponding to the self-compacting concrete-(SCC). This research aims to study the effect of the internal curing using saturated lightweight aggregate- (LWA) on the steel reinforcing corrosion in SCC. In this research, crushed bricks or thermostone were partially replaced by (20%) by the weight of sand and volumetrically measured. The results showed that the steel reinforcement of internally cured concrete showed a slight increase in corrosion up to 300 days of exposure to the saline solution (containing 3.5% NaCl). The ability of using the crushed bricks or thermostone

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Publication Date
Wed Nov 14 2018
Journal Name
Fiber And Integrated Optics
Design Investigation of 2 × 2 Mach–Zehnder Optical Switch Based on a Metal–Polymer–Silicon Hybrid Plasmonic Waveguide
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In this paper, a miniaturized 2 × 2 electro-optic plasmonic Mach– Zehnder switch (MZS) based on metal–polymer–silicon hybrid waveguide is presented. Adiabatic tapers are designed to couple the light between the plasmonic phase shifter, implemented in each of the MZS arms, and the 3-dB input/output directional couplers. For 6 µm-long hybrid plasmonic waveguide supported by JRD1 polymer (r33= 390 pm/V), a π-phase shift voltage of 2 V is obtained. The switch is designed for 1550 nm operation wavelength using COMSOL software and characterizes by 2.3 dB insertion loss, 9.9 fJ/bit power consumption, and 640 GHz operation bandwidth

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Publication Date
Mon Sep 23 2019
Journal Name
Baghdad Science Journal
A Semi-Supervised Machine Learning Approach Using K-Means Algorithm to Prevent Burst Header Packet Flooding Attack in Optical Burst Switching Network
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Optical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm

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